Abstract Dialectical Frameworks (ADFs) are a natural generalization of Dung-styleargumentation frameworks. They are not restricted to the notion of attack, but alsodeal with supporting, dependent and redundant relations between arguments. Thisgeneralization makes ADFs more expressive at the cost of increased computationalcomplexity. There are some algorithmic advances to tackle this increased complexity,but only little work on parallel algorithms. The goal of this thesis is to illustrate thatparallelization is a viable approach to further improve ADF systems. By looking atmodern multi-core CPUs, we deem parallel algorithms as necessary to fully utilize currentand future hardware developments and thus making ADF systems future-proof.The advances towards parallel algorithms result in a concrete implementation of an ADFsystem. This system is capable of computing common reasoning tasks for many semanticsby choice either sequentially or in parallel. To keep the implementation overhead low andthe system extensible for further semantics, a new algorithmic model is introduced. Thismodel is based on shared conceptual building blocks between semantics. These buildingblocks only have to be implemented once and can then be used by each semantics. Itwas also designed with concurrent execution in mind, since many building blocks can beused by both execution models with only little changes.The thesis also provides some experiments to illustrate the benefits of parallel execution.It also provides technical discussions and insights on problems that may occur whenrunning things in parallel. This then concludes with an overview of possible futuredevelopments of this system to overcome these problems, but also suggestions on howADF systems may be improved in general.